Chances are you have never heard of Didier Sornette. Chances are that the next time you hear of him, you will be significantly poorer — unless you listen to what he says now.

Sornette is the professor of entrepreneurial risks at the Swiss Federal Institute of Technology (ETH Zurich). His research focuses of the prediction of crisis and extreme events in complex systems. His work covers earthquake physics, dynamics of success on social networks and complex system approach to medicine. However, the part that attracts market attention is what he does at the Financial Crisis Observatory, which is to test the hypothesis that financial "bubbles" can be diagnosed in real time and their termination predicted probabilistically.

In other words, he attempts to find when the next big fall in the financial markets can occur.

The term "bubble" refers to a situation where excessive future expectations lead to rise in prices. Sornette identifies speculative bubbles as arising from a confluence of two factors — factors that drive initial demand — say, new technology or perception of reduced market risk. This is followed by "amplification mechanisms", where a large increase in asset price is followed by higher demand as investors think that further increases in price will follow. This "super-exponential" acceleration in prices due to a positive feedback (or "pro-cyclicality") leads to formation and then maturation of a bubble in finite time.

In other words, when expectations of growth rate itself grow, it leads to instability. Recent examples have been the crash of 2008 and the technology burst in 2000, among others. In Sornette's world, the cause of the crash is unimportant. His research suggests that crashes have an internal origin — the unrealistic rise in expectations — and external factors only serve as catalyst for the subsequent burst. So why is all this important?

Of Black Swans...

In 2001, Nassim Nicholas Taleb, quantitative trader and academician, published a book Fooled by Randomness where he outlined the theory of Black Swans. Taleb described black swans as events whose probability of occurrence was mathematically very low (like finding a black swan in a bevy of white swans). Taleb explained that these events occur with higher frequency than theory predicted, were hard to predict if not impossible to predict, and caused events of significant consequence and magnitude.

... and Dragon Kings

Sornette, on the other hand, makes an entirely contrary claim. Not only can he predict the probability of a bubble bursting, he can do it with remarkable accuracy and, of course, before the event! He calls these outlier events as Dragon Kings. He has graphs that show the predictions of the S&P 500 US Index, and oil prices — made before the crash in 2007-08. These and others can be found on the website of his Financial Crisis Observatory.

A Matter of Modelling

The broad basis of the prediction is based on "power law". Most models of market prices use the "normal" distribution to model price behaviour. This model underestimates risk. Studies suggest that a better model, especially when markets are leveraged — which they often are — is to apply the power law.

Sornette's model looks for "outof-control" growth in asset prices that vary from the power law. "When herding behaviour among investors ramps up, a stock's or index's growth rate can increase faster than exponentially, leading to more herding. This positive feedback brings the system to a tipping point. About two-thirds of the time, a crash results," says Sornette in a paper in 2009.

To break away from allegations that his forecasts are self-fulfilling — after all, market participants who believe his forecasts are likely to start positioning themselves accordingly, Sornette's team now makes forecast that are released in encrypted form on a website with a public key to decode the paper after the forecast period. His most recent prediction was a "Sell" signal on May 21 on the S&P 500, when his Crash Risk Index jumped up. The market was down 9.5% in a month after that.

Sornette recently made a presentation at TED Global 2013 — a talk worth viewing. The upshot of the presentation and the subsequent interview is that he continues to foresee bubbles in financial and insurance sectors, as well as construction and realty sectors in the US — the very same sectors that led the burst in 2008 in the first place.

Ironically, the success of a model can also lead to its demise as participants adjust their behaviour to include the forecasts of the model. Till this happens, Sornette's research needs to be taken seriously.